# Copyright 2021 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================
"""Mindspore quantum simulator operator."""

from mindspore.ops.primitive import PrimitiveWithInfer
from mindspore.ops.primitive import prim_attr_register
from mindspore._checkparam import Validator as validator
from mindspore.common import dtype as mstype
from mindspore.ops._grad.grad_base import bprop_getters
import mindspore.ops as P
from mindquantum.circuit import Circuit
from mindquantum.gate import Hamiltonian
from mindquantum.gate import Projector
from mindquantum.ops import QubitOperator
from ._check_qnn_input import _check_type_or_iterable_type
from ._check_qnn_input import _check_circuit
from ._check_qnn_input import _check_parameters_of_circuit


class PQC(PrimitiveWithInfer):
    r"""
    Evaluate a parameterized quantum circuit and calculate the gradient of each parameters.

    Inputs of this operation is generated by MindQuantum framework.

    Inputs:
        - **n_qubits** (int) - The qubit number of quantum simulator.
        - **encoder_params_names** (list[str]) - The parameters names of encoder circuit.
        - **ansatz_params_names** (list[str]) - The parameters names of ansatz circuit.
        - **gate_names** (list[str]) - The name of each gate.
        - **gate_matrix** (list[list[list[list[float]]]]) - Real part and image part of the matrix of quantum gate.
        - **gate_obj_qubits** (list[list[int]]) - Object qubits of each gate.
        - **gate_ctrl_qubits** (list[list[int]]) - Control qubits of each gate.
        - **gate_params_names** (list[list[str]]) - Parameter names of each gate.
        - **gate_coeff** (list[list[float]]) - Coefficient of eqch parameter of each gate.
        - **gate_requires_grad** (list[list[bool]]) - Whether to calculate gradient of parameters of gates.
        - **hams_pauli_coeff** (list[list[float]]) - Coefficient of pauli words.
        - **hams_pauli_word** (list[list[list[str]]]) - Pauli words.
        - **hams_pauli_qubit** (list[list[list[int]]]) - The qubit that pauli matrix act on.
        - **is_projector** (bool) - Whether the measurement operator is a subspace bitstring measurement.
        - **projectors** (Union[str, list[str]]) - The projector bitstrings.
        - **n_threads** (int) - Thread to evaluate input data.

    Outputs:
        - **expected_value** (Tensor) - The expected value of hamiltonian.
        - **g1** (Tensor) - Gradient of encode circuit parameters.
        - **g2** (Tensor) - Gradient of ansatz circuit parameters.

    Supported Platforms:
        ``CPU``
    """
    @prim_attr_register
    def __init__(self, n_qubits, encoder_params_names, ansatz_params_names,
                 gate_names, gate_matrix, gate_obj_qubits, gate_ctrl_qubits,
                 gate_params_names, gate_coeff, gate_requires_grad,
                 hams_pauli_coeff, hams_pauli_word, hams_pauli_qubit,
                 is_projector, projectors, n_threads):
        """Initialize PQC"""
        self.init_prim_io_names(
            inputs=['encoder_data', 'ansatz_data'],
            outputs=['results', 'encoder_gradient', 'ansatz_gradient'])
        if is_projector:
            self.n_meas = len(projectors)
        else:
            self.n_meas = len(hams_pauli_coeff)

    def check_shape_size(self, encoder_data, ansatz_data):
        if len(encoder_data) != 2:
            raise ValueError(
                "PQC input encoder_data should have dimension size \
equal to 2, but got {}.".format(len(encoder_data)))
        if len(ansatz_data) != 1:
            raise ValueError(
                "PQC input ansatz_data should have dimension size \
equal to 1, but got {}.".format(len(ansatz_data)))

    def infer_shape(self, encoder_data, ansatz_data):
        self.check_shape_size(encoder_data, ansatz_data)
        return [encoder_data[0], self.n_meas], [
            encoder_data[0], self.n_meas,
            len(self.encoder_params_names)
        ], [encoder_data[0], self.n_meas,
            len(self.ansatz_params_names)]

    def infer_dtype(self, encoder_data, ansatz_data):
        args = {'encoder_data': encoder_data, 'ansatz_data': ansatz_data}
        validator.check_tensors_dtypes_same_and_valid(args, mstype.float_type,
                                                      self.name)
        return encoder_data, encoder_data, encoder_data


@bprop_getters.register(PQC)
def bprop_pqc(self):
    """Grad definition for `PQC` operation."""
    t = P.Transpose()
    mul = P.Mul()
    sum_ = P.ReduceSum()

    def bprop(encoder_data, ansatz_data, out, dout):
        dx = t(out[1], (2, 0, 1))
        dx = mul(dout[0], dx)
        dx = sum_(dx, 2)
        dx = t(dx, (1, 0))
        dy = P.tensor_dot(dout[0], out[2], ((0, 1), (0, 1)))
        return dx, dy

    return bprop


def generate_pqc_operator(encoder_params_names,
                          ansatz_params_names,
                          circuit: Circuit,
                          measurements,
                          n_threads=1):
    """
    A method to generate a parameterized quantum circuit simulation operator.

    Args:
        encoder_params_names (list[str]): The list of parameter names for
            encoder circuit.
        ansatz_params_names (list[str]): The list of parameter names for ansatz
            circuit.
        circuit (Circuit): The whole circuit combined with
            encoder circuit and ansatz circuit.
        measurements (Union[Hamiltonian, list[Hamiltonian], Projector, list[Projector]]): The measurement
            operators, would be hamiltonians or projectors.
        n_threads (int): Number of threads for data parallelize.

    Returns:
        PQC, A parameterized quantum circuit simulator operator supported by mindspore framework.

    Examples:
        >>> from mindquantum.ops import QubitOperator
        >>> from mindquantum import Circuit
        >>> import mindquantum.gate as G
        >>> encoder_circ = Circuit([G.RX('a').on(0)])
        >>> ansatz_circ = Circuit([G.RY('b').on(0)])
        >>> circ = encoder_circ + ansatz_circ
        >>> ham = G.Hamiltonian(QubitOperator('Z0'))
        >>> pqc = generate_pqc_operator(['a'], ['b'], circ, ham)
    """
    _check_circuit(circuit, 'Circuit')
    _check_type_or_iterable_type(measurements, (Hamiltonian, Projector),
                                 'Hamiltonian or Projector')
    _check_parameters_of_circuit(encoder_params_names, ansatz_params_names,
                                 circuit)
    if not isinstance(n_threads, int) or n_threads <= 0:
        raise TypeError(
            "n_threads requires a positive int, but get {}".format(n_threads))
    if circuit.n_qubits == -1:
        circuit.summary(False)
    is_projector = False
    if isinstance(measurements, (Projector, Hamiltonian)):
        measurements = [measurements]
    hams = [Hamiltonian(QubitOperator())]
    pros = [Projector('')]
    if isinstance(measurements[0], Hamiltonian):
        hams = measurements
    if isinstance(measurements[0], Projector):
        for pro in measurements:
            if pro.n_qubits != circuit.n_qubits:
                raise ValueError(
                    f"The qubit of projector {pro} not match with quantum circuit."
                )
        is_projector = True
        pros = measurements
    ham_ms_data = {}
    for ham in hams:
        for k, v in ham.mindspore_data().items():
            if k not in ham_ms_data:
                ham_ms_data[k] = [v]
            else:
                ham_ms_data[k].append(v)
    proj_ms_data = {}
    for pro in pros:
        for k, v in pro.mindspore_data().items():
            if k not in proj_ms_data:
                proj_ms_data[k] = [v]
            else:
                proj_ms_data[k].append(v)
    return PQC(circuit.n_qubits,
               encoder_params_names=encoder_params_names,
               ansatz_params_names=ansatz_params_names,
               **circuit.mindspore_data(),
               **ham_ms_data,
               is_projector=is_projector,
               **proj_ms_data,
               n_threads=n_threads)
